class_docstr: Swap-in HDF4 File Handler.
docstr: Mimic reader input file content.
docstr_tok: ["Mimic","reader","input","file","content","."]
code: def get_test_content(self, filename, filename_info, filetype_info):
      """Mimic reader input file content."""
      file_content = {
          "/attr/platform": "SNPP",
          "/attr/sensor": "VIIRS",
      }
  
      file_content["longitude"] = xr.DataArray(
          da.from_array(DEFAULT_LON_DATA, chunks=4096),
          attrs={
              "_FillValue": np.nan,
              "scale_factor": 1.0,
              "add_offset": 0.0,
              "standard_name": "longitude",
          },
      )
      file_content["longitude/shape"] = DEFAULT_FILE_SHAPE
  
      file_content["latitude"] = xr.DataArray(
          da.from_array(DEFAULT_LAT_DATA, chunks=4096),
          attrs={
              "_FillValue": np.nan,
              "scale_factor": 1.0,
              "add_offset": 0.0,
              "standard_name": "latitude",
          },
      )
      file_content["latitude/shape"] = DEFAULT_FILE_SHAPE
  
      file_content["variable1"] = xr.DataArray(
          da.from_array(DEFAULT_FILE_DATA, chunks=4096).astype(
              np.float32
          ),
          attrs={
              "_FillValue": -1,
              "scale_factor": 1.0,
              "add_offset": 0.0,
              "units": "1",
          },
      )
      file_content["variable1/shape"] = DEFAULT_FILE_SHAPE
  
      # data with fill values
      file_content["variable2"] = xr.DataArray(
          da.from_array(DEFAULT_FILE_DATA, chunks=4096).astype(
              np.float32
          ),
          attrs={
              "_FillValue": -1,
              "scale_factor": 1.0,
              "add_offset": 0.0,
              "units": "1",
          },
      )
      file_content["variable2/shape"] = DEFAULT_FILE_SHAPE
      file_content["variable2"] = file_content["variable2"].where(
          file_content["variable2"] % 2 != 0
      )
  
      # category
      file_content["variable3"] = xr.DataArray(
          da.from_array(DEFAULT_FILE_DATA, chunks=4096).astype(np.byte),
          attrs={
              "SCALED": 0,
              "_FillValue": -128,
              "flag_meanings": "clear water supercooled mixed ice unknown",
              "flag_values": [0, 1, 2, 3, 4, 5],
              "units": "none",
          },
      )
      file_content["variable3/shape"] = DEFAULT_FILE_SHAPE
  
      return file_content
  
imports: import os
  import unittest
  from unittest import mock
  import dask.array
  import numpy
  import pytest
  import xarray
  from pyresample.geometry import AreaDefinition, SwathDefinition
  from satpy.tests.reader_tests.test_hdf4_utils import FakeHDF4FileHandler
label_desc: Use image node_id 1 for calling the FakeHDF4FileHandlerPolar obj's underlying member method code with example usage: obj.get_test_content(filename, filename_info, filetype_info) and returns: file_content